Predicting Carbon Monoxide Concentrations in the Air of Pardis City,Iran, Using an Artificial Neural Network

To date, several methods have been proposed to explain the complex process of air pollution prediction. One of these methods uses neural networks. Artificial neural networks (ANN) are a branch of artificial intelligence, and because of their nonlinear mathematical structures and ability to provide acceptable forecasts, they have gained popularity among researchers. The goal of our study as documented in this article was to compare the abilities of two different ANNs, the multilayer perceptron (MLP) and radial basis function (RBF) neural networks, to predict carbon monoxide (CO) concentrations in the air of Pardis City, Iran. For the study, we used data collected hourly on temperature, wind speed, and humidity as inputs to train the networks. The MLP neural network had two hidden layers that contained 13 neurons in the first layer and 25 neurons in the second layer and reached a mean bias error (MBE) of 0.06. The coefficient of determination (R²), index of agreement (IA), and the Nash–Scutcliffe efficiency (E) between the observed and predicted data using the MLP neural network were 0.96, 0.9057, and 0.957, respectively. The RBF neural network with a hidden layer containing 130 neurons reached an MBE of 0.04. The R², IA, and E between the observed and predicted data using the RBF neural network were 0.981, 0.954, and 0.979, respectively. The results provided by the RBF neural network had greater acceptable accuracy than was the case with the MLP neural network. Finally, the results of a sensitivity analysis using the MLP neural network indicated that temperature is the primary factor in the prediction of CO concentrations and that wind speed and humidity are factors of second and third importance when forecasting CO levels.     

HYDROLOGICAL AND GEOCHEMICAL TRENDS AND PATTERNS IN THE UPPER RIO GRANDE, 1975 TO 19991

ABSTRACT: Hydrological and geochemical spatial patterns and temporal trends were analyzed using U.S. Geological Survey (USGS) water quality data collected from 1975 to 1999 along the uppermost 600 km of the Rio Grande in Colorado and New Mexico. Data on discharge, specific conductivity (SC), total dissolved solids (TDS), pH, Ca²⁺, Na⁺, Mg²⁺, K⁺, HCO₃^?, SO₄^2‐, Cl^?, F^?, and SiO₂ came from six USGS stations ranging from the Colorado‐New Mexico border to below Albuquerque, New Mexico. Linear regression, Kendall's S, and Seasonal Kendall's S’ were used to detect trends, and ANOVA was used to analyze spatial differences between stations. Statistically significant increasing trends occurred in SC, TDS, Ca²⁺, Na⁺, Mg²⁺, K⁺, Cl^?, and F^?in the uppermost reaches, and significant decreasing trends of SC, TDS, Ca²⁺, Mg²⁺, K⁺, HCO₃^?, and SO₄^2‐occurred at the lower stations around Albuquerque. Both fluoride concentrations and pH values increased at and below Albuquerque over the study period. Discharge data show an increasing trend across all stations. Spatially, data for dissolved substances show generally linear upstream to downstream increases in concentrations in the upper four stations, with several notable nonlinear increases at and below Albuquerque (SC, TDS, Na⁺, Cl^?). Significant increases in pH appear at and below Albuquerque, relative to upstream stations, probably due to improved sewage treatment.     

Upstream Sediment‐Control Dams: Five Decades of Experience in the Rapidly Eroding Dahan River Basin,Taiwan

Sedimentation is emerging as a key issue in sustainable reservoir management. One approach to controlling reservoir sedimentation is to trap sediment in hydraulic structures upstream of the reservoir. In the 1,163‐km² catchment of the Dahan River (Taiwan) over 120 “sabo” dams were built to reduce sediment yield to Shihmen Reservoir. Built in 1963 for water supply, Shihmen has lost over 40% of its 290‐Mm³ storage capacity to sedimentation. Most of these upstream structures were small, but three had capacities >9 Mm³. Field measurements and historical data from the Water Resources Agency show most smaller dams had filled with sediment by 1976. The three largest were full or nearly so by 2007, when one (Barlin Dam) failed, releasing a pulse of 7.5 Mm³, most of its 10.4 Mm³ stored sediment downstream. The Central Range of Taiwan is rapidly eroding (denudation rates 3‐6 mm/yr), so geologically high loads make sediment problems manifest sooner. Even in other environments, however, eventually small dams built upstream of large reservoirs are likely to fill themselves, creating multiple small sediment‐filled reservoirs, some located in sites inaccessible to mechanical removal. Our analysis suggests sabo dams do not offer a long‐term basis for controlling reservoir sedimentation in such a high‐sediment yield environment. Sustainable solutions must somehow pass sediment downstream, as would be accomplished by a sediment bypass around Shihmen Reservoir, as now being studied.     

GROUND WATER FLOW AND RUNOFF IN A COASTAL PLAIN STREAM1

ABSTRACT: The quantity, seasonality, and sources of flow were analyzed for two segments of Four Mile Branch, a small stream on the Coastal Plain of South Carolina using data obtained from USGS gauging stations. Flows in the “upstream segment,” a 12.6-km² watershed comprising the head waters of Four Mile Branch, averaged 0.129 m³ s^?1 and showed a distinctly seasonal pattern, with maximum flows in February and March and minimum flows in September and October. Inflow to the “downstream segment,” a 2.2-km² watershed associated with the main channel, averaged 0.059 m³ s^?1 and showed no seasonal patterns. Discharges per unit area of watershed were greater for the downstream segment, 0.83 m³ per year per m² of land surface, than for the upstream segment, 0.32 m³ per year per m². The differences in discharge rates and seasonalities between the two segments reflect differences in aquifers supplying the different segments. Analyses of Streamflow by hydrograph separation and Streamflow partitioning methods indicated that greater than 90 percent of the flows in the upstream and downstream segments were due to ground water-driven base flows.     

Flood Forecasting Using Neural Computing Techniques and Conceptual Class Segregation

Various neural networks models are developed and applied for flood forecasting at Sangye station (no. 1) of the Bocheong Stream catchment, which is one of the International Hydrological Program's representative catchments, Republic of Korea. The neural networks models (NNMs) are multilayer perceptron‐neural networks model (MLP‐NNM), generalized regression neural networks model (GRNNM), and Kohonen self‐organizing feature maps neural networks model (KSOFM‐NNM). Data used for model training and testing are divided into two groups: such as floods and typhoon events. Single conventional application and class segregation implementation are applied to evaluate the neural networks models. KSOFM‐NNM forecasts flood discharge more accurately than do MLP‐NNM and GRNNM for the testing data of Methods I and II for single conventional application and class segregation implementation. This study shows that class segregation can capture the dynamics of different physical processes and overcome the difficulties using single conventional application of neural networks models.     

A HYBRID COMPUTER PROGRAM FOR PREDICTING THE CHEMICAL QUALITY OF IRRIGATION RETURN FLOWS1

ABSTRACT. A hybrid computer program was developed to predict the water and salt outflow from a river basin in which irrigation is the major user of water. The model combines a chemical model which predicts the quality of water percolated through a soil profile with a general hydrologic model. The chemical model considers the reactions that occur in the soil, including the exchange of calcium, magnesium, and sodium cations on the soil complex, and the dissolution and precipitation of gypsum and lime. The chemical composition of the outflow is a function of these chemical processes within the soil, plus the blending of undiverted inflows, evaporation, transpiration, and the mixing of sub surface return flows with groundwater. The six common ions of western waters, namely calcium (Ca⁺⁺), magnesium (Mg⁺⁺), sodium (Na⁺), sulfate (SO₄⁼), chloride (Cl^?), and bicarbonate (HCO₃^?) were considered in the study. Total dissolved solids (TDS) outflow was obtained by adding the individual ions. The overall model operates on a monthly time unit. The model was tested on a portion of the Little Bear River basin in northern Utah. The model successfully simulated measured outflows of water and each of the six ions for a 24-month period. The usefulness of the model was demonstrated by a management study of the prototype system. For example, preliminary results indicated that the available water supply could be used to irrigate additional land without unduly increasing the salt outflow from the basin. With minor adjustments the model can be applied to other hydrologic areas.     

Hydrochemistry of drinking water sources and water purifiers in relation to epidemiological study in Hisar,North-West India

The concern related to the drinking of reverse osmosis (RO) water containing low levels of minerals is growing day by day. This study involves the analysis of water samples from various drinking water sources in a rural site, Mirchpur village, an Indus Valley civilization site (grid location: 29° 18′ 42.3″ N, 76° 10′ 33.0″ E) of Hisar, India, along with the health survey of human subjects. The hydrochemistry of water collected from hand pumps, river canals, tube wells, submersibles, and the RO systems installed in various homes was explored for pH, EC, TH, TDS, turbidity, cations (Na⁺, Ca²⁺, Mg²⁺), anions (CO₃²⁻, HCO₃⁻, Cl⁻, SO₄²⁻, NO₃⁻, F⁻), and elements (Fe, Pb, Se) employing the ion chromatography, flame photometry, and ICP-AES techniques. Lead (Pb) and Selenium (Se) were detected in trace amounts (0.30–2.6 μg L⁻¹; 0.10–4.1 μg L⁻¹, respectively) in all the samples, including the samples collected from RO purifiers, but Iron (Fe) was not detected in RO samples even in trace amounts. The F-levels in hand pump water (HPW) and submersible water (SW) (1.9  and 1.7 mg L⁻¹, respectively) and TDS levels in SW (3048 mg L⁻¹) were found to be above WHO and BIS safe limits. TDS levels in the river canal (900 mg L⁻¹), tube well (1104 mg L⁻¹), hand pump (1170 mg L⁻¹), and submersible samples (3048 mg L⁻¹) were found significantly higher as compared to the RO personal water (ROPW; 216 mg L⁻¹) and RO supply water (ROSW; 90 mg L⁻¹). The collected epidemiological data reveals that 21%, 19%, 13%, and 12% of natives reported skin, kidney, hair fall, liver, and stomach issues, respectively, suspecting the crucial role of high TDS and fluoride levels in the area. This study also provides a comparison between the quality of RO and the direct supply water, along with correlation matrices for different parameters, which gives a rationale for the limitations of drinking direct supply water without any purification and RO water containing low mineral content.     

Dams in the Amazon: Belo Monte and Brazil’s Hydroelectric Development of the Xingu River Basin

Hydroelectric dams represent major investments and major sources of environmental and social impacts. Powerful forces surround the decision-making process on public investments in the various options for the generation and conservation of electricity. Brazil’s proposed Belo Monte Dam (formerly Kararaô) and its upstream counterpart, the Altamira Dam (better known by its former name of Babaquara) are at the center of controversies on the decision-making process for major infrastructure projects in Amazonia. The Belo Monte Dam by itself would have a small reservoir area (440 km²) and large installed capacity (11, 181.3 MW), but the Altamira/Babaquara Dam that would regulate the flow of the Xingu River (thereby increasing power generation at Belo Monte) would flood a vast area (6140 km²). The great impact of dams provides a powerful reason for Brazil to reassess its current policies that allocate large amounts of energy in the country’s national grid to subsidized aluminum smelting for export. The case of Belo Monte and the five additional dams planned upstream (including the Altamira/Babaquara Dam) indicate the need for Brazil to reform its environmental assessment and licensing system to include the impacts of multiple interdependent projects.     

On the Role of Spatial,Temporal, and Climatic Forces on Stream Sediment Loading from Rural and Urban Ecosystems

In this study, we characterize the greatest sediment loading events by their sediment delivery behavior; dominant climate, watershed, and antecedent conditions; and their seasonal distribution for rural and urban land uses. The study area is Paradise Creek Watershed, a mixed land use watershed in northern Idaho dominated by saturation excess processes in the upstream rural area and infiltration excess in the downstream urban area. We analyzed 12 years of continuous streamflow, precipitation, and watershed data at two monitoring stations. We identified 137 sediment loading events in the upstream rural section of the watershed and 191 events in the downstream urban section. During the majority of these events conditions were transport limited and the sediment flush occurred early in the event, generally in the first 20% of elapsed event time. Statistical analysis including two dozen explanatory variables showed peak discharge, event duration, and antecedent baseflow explained most of the variation in event sediment load at both stations and for the watershed as a whole (R² = 0.73‐0.78). In the rural area, saturated soils combined with spring snowmelt in March led to the greatest loading events. The urban area load contribution peaked in January, which could be a re‐suspension of streambed sediments from the previous water year. Throughout the study period, one event contributed, on average, 33% of the annual sediment load but only accounted for 2% of the time in a year.     

Groundwater characterization in major industrial and residential locations of Lagos metropolis

This study investigated the quality of groundwater collected from two industrial and residential locations, each within the Lagos metropolis. Prescribed standard procedures of the American Public Health Association (APHA) were used to measure the physicochemical parameters of each of the groundwater samples, which include pH, electrical conductivity (EC), dissolved oxygen, total dissolved solids (TDS), biological oxygen demand, chemical oxygen demand; the anions chloride (Cl^?), nitrate (NO₃^?), sulfate (SO₄^?), and phosphate (PO₄^?); and heavy metals copper (Cu), zinc (Zn), lead (Pb), manganese (Mn), iron (Fe), cobalt (Co), cadmium (Cd), and chromium (Cr). Based on the laboratory analysis, the physicochemical parameters that were measured were within the permissible ranges specified by the World Health Organization and the Nigerian Standard for Drinking Water Quality Standards Organization of Nigeria (SON), except for pH, TDS, EC, Pb, Mn, and Fe for groundwater samples from the industrial locations and for pH, Pb, Mn, and Fe for residential locations. The elevated concentrations of TDS and EC reported for groundwater samples from industrial locations were attributed to the heavy discharge of effluents from nearby industrial treatment plants as well as the dissolution of ionic heavy metals from industrial activities involving the use of heavy machines. Statistical analysis using Pearson's correlation revealed the physicochemical parameters to be moderately and strongly correlated with one another at either p < .05 or < .01. In conclusion, groundwater samples from residential locations are more suitable for drinking than those from industrial locations.     

Evolving Expectations of Dam Removal Outcomes: Downstream Geomorphic Effects Following Removal of a Small,Gravel‐Filled Dam1

Kibler, Kelly, Desiree Tullos, and Mathias Kondolf, 2011. Evolving Expectations of Dam Removal Outcomes: Downstream Geomorphic Effects Following Removal of a Small, Gravel‐Filled Dam. Journal of the American Water Resources Association (JAWRA) 1‐16. DOI: 10.1111/j.1752‐1688.2011.00523.x Abstract: Dam removal is a promising river restoration technique, particularly for the vast number of rivers impounded by small dams that no longer fulfill their intended function. As the decommissioning of small dams becomes increasingly commonplace in the future, it is essential that decisions regarding how and when to remove these structures are informed by appropriate conceptual ideas outlining potential outcomes. To refine predictions, it is necessary to utilize information from ongoing dam removal monitoring to evolve predictive tools, including conceptual models. Following removal of the Brownsville Dam from the Calapooia River, Oregon, aquatic habitats directly below the dam became more heterogeneous over the short term, whereas changes further downstream were virtually undetectable. One year after dam removal, substrates of bars and riffles within 400 m downstream of the dam coarsened and a dominance of gravel and cobble sediments replaced previously hardpan substrate. New bars formed and existing bars grew such that bar area and volume increased substantially, and a pool‐riffle structure formed where plane‐bed glide formations had previously dominated. As the Brownsville Dam stored coarse rather than fine sediments, outcomes following removal differ from results of many prior dam removal studies. Therefore, we propose a refined conceptual model describing downstream geomorphic processes following small dam removal when upstream fill is dominated by coarse sediments.     

ASSESSMENT USING GIS AND SEDIMENT ROUTING OF THE PROPOSED REMOVAL OF BALLVILLE DAM,SANDUSKY RIVER,OHIO1

ABSTRACT: The proposed removal of Ballville Dam was assessed by (1) using a new Geographic Information Systems (GIS) based method for calculating reservoir sediment storage, (2) evaluating sediment properties and contamination from core data, and (3) assessing downstream impacts from sediment routing calculations. A 1903 (pre‐dam) map was manipulated using GIS to recreate the reservoir bathymetry at time of dam construction and used in combination with a detailed 1993 bathymetric survey to calculate sediment volumes and thickness. Reservoir sediment properties and geochemistry were determined from 14 sediment vibracores. Annual sedimentation rates varied from 1.7 to 4.3 g/cm²/yr based on Cesium‐137 (¹³⁷Cs) and Lead‐210 (²¹⁰Pb) geochronology and dated flood layers. The pore fluid geochemistry (Ba, Co, Cu, Mn) of four cores showed surficial enrichments in Cu, while Co and Mn show secondary peaks within the sediments. GIS calculations showed that a designed channel through the former reservoir able to accommodate the 10 percent Probable Maximum Flood (PMF) would require removing approximately 0.35 million m³ of sediment (27 percent of the reservoir fill), either by dredging at a cost of up to $6.3 million or by releasing fine grained sediment downstream. A sediment routing model was applied for the critical 6 km downstream using four cross sections. The sediment routing model predicts that, for flows exceeding minimum Mean Daily Flow (1924 to 1998 data), greater than 90 percent of this sediment would be transported through downstream reaches into Lake Erie (Sandusky Bay).     

Application of Multivariate Statistical Methods and Water-Quality Index to Evaluation of Water Quality in the Kashkan River

The Kashkan River (KR), located in the west of Iran, is a major source of water supply for residential and agricultural areas as well as livestock. The objective of this study was to assess the spatial and long temporal variations of surface water quality of the KR based on measured chemical ions. The Canadian Council of Ministers of Environment Water Quality Index (CCME WQI) technique was utilized using measurements from 10 sampling stations during a period of 36 years (1974–2009). The measured data included cations (Na⁺, K⁺, Ca²⁺, Mg²⁺), anions (HCO₃ ^?, Cl^?, SO₄ ^2?), pH, and electrical conductivity. Principal component analysis was performed to identify which of the parameters to be included in the CCME WQI calculations were actually correlated and which ones were responsible for most of the variance observed in the water-quality data. In addition, KR water quality was evaluated for its suitability for drinking and irrigation purposes using conventional methods. Last, trend detection in the WQI time series of the KR showed water-quality degradation at all sampling stations, whereas the Jelhool sub-basin more adversely affects the quality of KR water in the watershed. Nonetheless, on average, the water quality of the KR was rated as fair.     

Comparison of the Performance of Statistical Models in Forecasting Monthly Total Dissolved Solids in the Rio Grande1

Abudu, S., J.P. King, Z. Sheng, 2011. Comparison of the Performance of Statistical Models in Forecasting Monthly Total Dissolved Solids in the Rio Grande. Journal of the American Water Resources Association (JAWRA) 48(1): 10‐23. DOI: 10.1111/j.1752‐1688.2011.00587.x Abstract: This paper presents the application of autoregressive integrated moving average (ARIMA), transfer function‐noise (TFN), and artificial neural networks (ANNs) modeling approaches in forecasting monthly total dissolved solids (TDS) of water in the Rio Grande at El Paso, Texas. Predictability analysis was performed between the precipitation, temperature, streamflow rates at the site, releases from upstream reservoirs, and monthly TDS using cross‐correlation statistical tests. The chi‐square test results indicated that the average monthly temperature and precipitation did not show significant predictability on monthly TDS series. The performances of one‐ to three‐month‐ahead model forecasts for the testing period of 1984‐1994 showed that the TFN model that incorporated the streamflow rates at the site and Caballo Reservoir release improved monthly TDS forecasts slightly better than the ARIMA models. Except for one‐month‐ahead forecasts, the ANN models using the streamflow rates at the site as inputs resulted in no significant improvements over the TFN models at two‐month‐ahead and three‐month‐ahead forecasts. For three‐month‐ahead forecasts, the simple ARIMA showed similar performance compared to all other models. The results of this study suggested that simple deseasonalized ARIMA models could be used in one‐ to three‐month‐ahead TDS forecasting at the study site with a simple, explicit model structure and similar model performance as the TFN and ANN models for better water management in the Basin.     

Experimental investigation of adsorption capacity of anthill in the removal of heavy metals from aqueous solution

In the present work, the adsorption capacity of anthill was investigated as a low‐cost adsorbent to remove the heavy metal ions, lead (II) ion (Pb²⁺), and zinc (II) ion (Zn²⁺) from an aqueous solution. The equilibrium adsorption isotherms of the heavy metal ions were investigated under batch process. For the study we examined the effect of the solution's pH and the initial cations concentrations on the adsorption process under a fixed contact time and temperature. The anthill sample was characterized using a scanning electron microscope (SEM), X‐ray fluorescence (XRF), and Fourier transform infrared (FTIR) techniques. From the SEM analysis, structural change in the adsorbent was a result of heavy metals adsorption. Based on the XRF analysis, the main composition of the anthill sample was silica (SiO₂), alumina (Al₂O₃), and zirconia (ZrO₂). The change in the peaks of the spectra before and after adsorption indicated that there was active participation of surface functional groups during the adsorption process. The experimental data obtained were analyzed using 2‐ and 3‐parameter isotherm models. The isotherm data fitted very well to the 3‐parameter Radke–Prausnitz model. It was noted that Pb²⁺ and Zn²⁺ can be effectively removed from aqueous solution using anthill as an adsorbent.     

Evaluation of groundwater and soil pollution in a landfill area using electrical resistivity imaging survey

Landfills are sources of groundwater and soil pollution due to the production of leachate and its migration through refuse. This study was conducted in order to determine the extent of groundwater and soil pollution within and around the landfill of Seri Petaling located in the State of Selangor, Malaysia. The condition of nearby surface water was also determined. An electrical resistivity imaging survey was used to investigate the leachate production within the landfill. Groundwater geochemistry was carried out and chemical analysis of water samples was conducted upstream and downstream of the landfill. Surface water was also analyzed in order to determine its quality. Soil chemical analysis was performed on soil samples taken from different locations within and around the landfill in the vadose zone (unsaturated zone) and below the water table (in the soil saturated zone). The resistivity image along line L–L₁ indicated the presence of large zones of decomposed waste bodies saturated with highly conducting leachate. Analysis of trace elements indicated their presence in very low concentrations and did not reflect any sign of heavy metal pollution of ground and surface water or of soil. Major ions represented by Na, K, and Cl were found in anomalous concentrations in the groundwater of the downstream bore hole, where they are 99.1%, 99.2%, and 99.4%, respectively, higher compared to the upstream bore hole. Electrical conductivity (EC) was also found in anomalous concentration downstream. Ca and Mg ions represent the water hardness (which is comparatively high downstream). There is a general trend of pollution towards the downstream area. Sulfates (SO₄) and nitrates (NO₃) are found in the area in low concentrations, even below the WHO standards for drinking water, but are significantly higher in the surface water compared to the groundwater. Phosphate (PO₄) and nitrite (NO₂), although present in low levels, are significantly higher at the downstream. There is no significant difference in the amount of fluoride (F) in the different locations. In the soil vadose zone, heavy metals were found to be in their typical normal ranges and within the background concentrations. Soil exchangeable bases were significantly higher in the soil saturated zone compared to the vadose zone, and no significant difference was obtained in the levels of inorganic pollutants. With the exception of Cd, the concentration ranges of all trace elements (Cu, Zn, Cr, Pb, and Ni) of Seri Petaling landfill soils were below the upper limits of baseline concentrations published from different sources.     

Modeling biological oxygen demand of the Melen River in Turkey using an artificial neural network technique

Artificial neural networks (ANNs) are being used increasingly to predict and forecast water resources' variables. The feed-forward neural network modeling technique is the most widely used ANN type in water resources applications. The main purpose of the study is to investigate the abilities of an artificial neural networks' (ANNs) model to improve the accuracy of the biological oxygen demand (BOD) estimation. Many of the water quality variables (chemical oxygen demand, temperature, dissolved oxygen, water flow, chlorophyll a and nutrients, ammonia, nitrite, nitrate) that affect biological oxygen demand concentrations were collected at 11 sampling sites in the Melen River Basin during 2001-2002. To develop an ANN model for estimating BOD, the available data set was partitioned into a training set and a test set according to station. In order to reach an optimum amount of hidden layer nodes, nodes 2, 3, 5, 10 were tested. Within this range, the ANN architecture having 8 inputs and 1 hidden layer with 3 nodes gives the best choice. Comparison of results reveals that the ANN model gives reasonable estimates for the BOD prediction.     

Evaluation of spatial and temporal variation in Karun River water quality during five decades (1968–2014)

In the present study, the multivariate statistical technique cluster analysis (CA) is used to evaluate the spatial and temporal variations in the water quality data for the Karun River, which was gathered during 46 years of monitoring (from 1968 to 2014). The data recorded electrical conductivity (EC) in the river at six water monitoring stations along its course. The mean of EC was 972.05 ± 365.466 micromhos per centimeter (μmhos/cm) at the most upstream station and showed an increase to 1458.41 ± 675.048 μmhos/cm at the most downstream of the stations. By using hierarchical CA, the six sampling stations were grouped into three clusters of similar characteristics, which may be a result of different land uses in proximity to the stations. Furthermore, two‐way analysis of variance showed that EC had a significant correlation (p < 0.001) with the season, and the mean of the pollution depended on the level of the cluster and the season (spring, summer, autumn, and winter).     

Hydrogeochemical and Isotopic Investigations on Groundwater Salinization in the Datong Basin,Northern China1

Abstract: Analyses of major elements, environmental isotope ratios (δ¹⁸O, δ²H), and PHREEQC inverse modeling investigations were conducted to understand the processes controlling the salinization of groundwater within the Datong Basin. The hydrochemical results showed that groundwater with high total dissolved solid (TDS) concentrations was dominated by sodium bicarbonate (Na‐HCO₃), sodium chlorite (Na‐Cl), and sodium sulfate (Na‐SO₄) type waters, whereas low‐TDS groundwater from near mountain areas was dominated by calcium bicarbonate (Ca‐HCO₃) and magnesium bicarbonate (Mg‐HCO₃) type waters. The characterization of the major components of groundwater and PHREEQC inverse modeling indicated that the aluminosilicate hydrolysis, cation exchange, and dissolution of evaporites (halite, mirabilite, and gypsum) governed the salinization of groundwater within the Datong Basin. The environmental isotope (δ¹⁸O, δ²H) and Cl^?/Br^? ratios revealed the impact of fast vertical recharge by irrigation returns and salt‐flushing water on the groundwater salinization. According to the analyses of major hydrochemical components and PHREEQC inverse modeling, evaporite dissolution associated with irrigation and salt‐flushing practice was probably the dominant controlling factor for the groundwater salinization, especially in the central part of the basin. Therefore, groundwater pumping for irrigation and salt‐flushing should be controlled to protect groundwater quality in this area.     

Dam Design can Impede Adaptive Management of Environmental Flows: A Case Study from the Opuha Dam, New Zealand

The Opuha Dam was designed for water storage, hydropower, and to augment summer low flows. Following its commissioning in 1999, algal blooms (dominated first by Phormidium and later Didymosphenia geminata) downstream of the dam were attributed to the reduced frequency and magnitude of high-flow events. In this study, we used a 20-year monitoring dataset to quantify changes associated with the dam. We also studied the effectiveness of flushing flows to remove periphyton from the river bed. Following the completion of the dam, daily maximum flows downstream have exceeded 100 m³ s^?1 only three times; two of these floods exceeded the pre-dam mean annual flood of 203 m³ s^?1 (compared to 19 times >100 m³ s^?1 and 6 times >203 m³ s^?1 in the 8 years of record before the dam). Other changes downstream included increases in water temperature, bed armoring, frequency of algal blooms, and changes to the aquatic invertebrate community. Seven experimental flushing flows resulted in limited periphyton reductions. Flood wave attenuation, bed armoring, and a shortage of surface sand and gravel, likely limited the effectiveness of these moderate floods. Floods similar to pre-dam levels may be effective for control of periphyton downstream; however, flushing flows of that magnitude are not possible with the existing dam infrastructure. These results highlight the need for dams to be planned and built with the capacity to provide the natural range of flows for adaptive management, particularly high flows.